We gathered an expert panel on this topic that includes perspectives from Sheenal Patel, Co-founder and CEO of NVN Hotels and Principal of Arbor Lodging Partners; Scott Openlander, COO and founder at (RE)meter; and David Kollmorgen,

David Kollmorgen

International Director and Leader of Business Intelligence at JLL Americas.

Margy Sweeney:Big data has transformed mass market businesses like retail, consumer banking and e-commerce. What is it doing for a relationship business like commercial real estate?

Scott Openlander: Commercial real estate data was historically fragmented and inaccurate which lead to slow and inaccurate risk analysis. If an asset manager wanted to underwrite a lease transaction, they would likely have to obtain data from a variety of sources including industry financial data, employment and census, and then manually combine, calculate and hope the results truly measured a tenant’s risk and

Sheenal Patel

their industry. However, today CRE technologies permit instant data convergence combined with analytics, which provides a fast and accurate assessment of lease risk and tenants industries. For example, using the (RE)meter TIL Score, clients enter or upload basic financial information related to the prospective tenant, choose the tenant’s industry and then enter lease terms. That data is then added to industry data in our system, and the TIL score and credit report is generated, empowering our clients to conduct data-driven financial analysis quickly. We can uniquely rate how much rent a tenant should pay based upon its industry and geographic area. (RE)meter exclusive industry data uses all 27.0 million private and public company IRS tax returns, so it is complete and accurate.

David Kollmorgen: Today’s platforms are light years ahead of where we were even five years ago. They can aggregate real estate data and provide human-friendly visualizations that create tangible impact that the C-Suite can put to work. From consolidating historical data, to visually modeling outcome forecasts and savings opportunities, executives in many companies now expect this real estate data to be included in data-driven business decision making. Data transparency and higher level analytics has inserted real estate into the C-Suite dialogue, and it’s thanks to advances in business intelligence.

Sheenal Patel: Coming from an investment banking background, since joining the hotel investment industry I’ve observed that there has been a ‘shoot from the hip’ kind of mentality. For me, delayed data and vague spreadsheets really don’t cut it, when we’re trying to uncover how to run a property more efficiently, or accurately calculate current ROI. We’ve put systems in place to obtain real time, accurate data very quickly using new technologies. That awareness allows us, as owners, to react quickly to changes in the data, pivot our strategies if necessary, and ultimately, increase returns.

Sweeney: How do you use data to drive tangible results and investment returns?

Patel: We get a lot of data inputs from our hotels that then inform multiple applications. Moving from excel to a dashboard system has completely changed the way we review our properties. For example, a lot of times it may be the same properties that are having small but frequent issues, and that stands out to us. If you can track those small things and start seeing trends, that’s where improvement opportunities are revealed.

Openlander: Nearly every landlord and investor out there has the opportunity, using new technologies, to make their leasing and investment decisions more data-driven than before. Data should answer tangible, relevant questions: Can the tenant afford the rent? Is the tenant’s industry growing and profitable? How does the lease transaction or credit affect the building’s value? Will the expected return of an asset be achieved? Our system uses Federal labor and establishment level statistics that demonstrate trends in supply and demand, and creates insights related to demand for space. We are able to rate and score the financial strength of local and national industries in minutes, which can be very telling. Landlords use this data to refine their focus on leasing and retaining stronger tenants in successful industries.

Sweeney: Many real estate professionals pride themselves on their instincts. How can the use of data improve decision-making without replacing the ‘gut instinct’ factor?

Kollmorgen: Data can provide a gut-check; that is, it can validate or refute what your instincts are telling you. Corporations are using data to determine how and where employees are working — and why. Once you confirm that, you have numbers to take to the C-Suite, not just an instinct or opinion. Using data and analytics to forecast workforce trends, fine-tune site selection strategies, or optimize a corporate real estate portfolio provides exactly the kind of information that the C-suite wants to know.

Openlander: It’s critical to understand the quality of your data; otherwise, you might think you’re making data-driven decisions, but you’re really just continuing to ‘go with your gut.’ Most private financial and lease data represents a small percentage of the market place, does not assess credit risk and is surveyed, volunteered and inaccurate. CRE companies should be consistently testing and supporting innovation as it leads to better returns. Making sure high quality data is integrated into a system is half the battle to understand risk and leasing decisions.

Sweeney: What does the future of CRE data look like, for the industry and your company?

Patel: Our systems will become even more turnkey and connected. Linking together our labor reporting tool and property management system, we expect to improve efficiencies and benefit from more insights. We also are cognizant of the benefits of having that real-time data front and center. In fact, we have plans to install more TV screens in our office so we can have our key performance indicators displayed constantly, so we can monitor the data in real-time.

Kollmorgen: In our new data and analytics platform, RED, the platform integrates data in a data warehouse, synchronizing key metrics such as property and cost types across multiple software applications. The future of corporate real estate data lies with the data scientists who will use this foundation, and ever growing data set, to uncover new insights—and turn them into improved financial and operational results for corporate real estate users, owners and investors.